Effectiveness of the chronic care model for adults with type 2 diabetes in primary care: a systematic review and meta-analysis

Background Mixed evidence exists regarding the effectiveness of the Chronic Care Model (CCM) with patient outcomes. The aim of this review is to examine the effectiveness of CCM interventions on hemoglobin A1c (HbA1c), systolic BP (SBP), diastolic BP (DBP), LDL cholesterol and body mass index (BMI) among primary care adults with type 2 diabetes. Methods PubMed, Embase, CINAHL, Cochrane Central Registry of Controlled Trials, Scopus and Web of Science were searched from January 1990 to June 2021 for randomized controlled trials (RCTs) comparing CCM interventions against usual care among adults with type 2 diabetes mellitus in primary care with HbA1c, SBP, DBP, LDL cholesterol and BMI as outcomes. An abbreviated search was performed from 2021 to April 2022. This study followed the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines for data extraction and Cochrane risk of bias assessment. Two reviewers independently extracted the data. Meta-analysis was performed using Review Manager software. Heterogeneity was evaluated using χ2 and I2 test statistics. Overall effects were evaluated using Z statistic. Results A total of 17 studies involving 16485 patients were identified. Most studies had low risks of bias. Meta-analysis of all 17 studies revealed that CCM interventions significantly decreased HbA1c levels compared to usual care, with a mean difference (MD) of −0.21%, 95% CI −0.30, −0.13; Z = 5.07, p<0.00001. Larger effects were experienced among adults with baseline HbA1c ≥8% (MD −0.36%, 95% CI −0.51, −0.21; Z = 5.05, p<0.00001) and when four or more CCM elements were present in the interventions (MD −0.25%, 95% CI −0.35, −0.15; Z = 4.85, p<0.00001). Interventions with CCM decreased SBP (MD −2.93 mmHg, 95% CI −4.46, −1.40, Z = 3.75, p=0.0002) and DBP (MD −1.35 mmHg, 95% CI −2.05, −0.65, Z = 3.79, p=0.0002) compared to usual care but there was no impact on LDL cholesterol levels or BMI. Conclusions CCM interventions, compared to usual care, improve glycaemic control among adults with type 2 diabetes in primary care, with greater reductions when the mean baseline HbA1c is ≥8% and with interventions containing four or more CCM elements. Systematic review registration PROSPERO CRD42021273959 Supplementary Information The online version contains supplementary material available at 10.1186/s13643-022-02117-w.


Background
Chronic diseases are increasing globally and have a significant impact on primary health services. Diabetes in particular is a complex disease that has considerable complications related to cardiovascular morbidities, thus leading to a poor quality of life [1,2]. The global diabetes prevalence in adults in 2021 was estimated to be 10.5%, approximately 537 million adults, with the figure rising to 12.2% at 783 million by 2045 [3]. In that year, diabetes caused 6.7 million deaths and caused at least USD 966 billion dollars in health expenditures, with 9% of total spending on adults. People with chronic conditions have multifaceted and complex needs that require continuity, comprehensiveness and coordination, of which primary care can play a central role in effective management and care integration [4]. However, patients often receive inadequate care with limited physician engagement in disease management as well as little coordination and communication among care providers [5].
Integrated care models are found to be effective in reducing health care costs and hospitalizations [6][7][8][9], besides enhancing patient satisfaction, increasing perceived quality of care and enabling access to services [10]. The 2022 American Diabetes Association (ADA) Standards of Medical Care in Diabetes [11] recommended that the approach to diabetes management in primary care be aligned with the Chronic Care Model (CCM), which emphasizes person-centred team care, integrated longterm treatment approaches to diabetes and comorbidities, and ongoing collaborative communication and goal setting between all team members. The CCM centred in primary care was developed by Wagner in the 1990s and has been shown to provide the best evidence-based framework for organizing and optimizing diabetes care delivery by modifying essential healthcare system elements to support high-quality patient-centred management [12][13][14]. These six elements are the organization of the healthcare delivery system, community linkages or resources, self-management support, decision support, delivery system design and clinical information systems and have been used as interventions to show improvement in diabetes care [15][16][17][18]. The CCM elements are described as follows, based on a published description [19]: Organization of healthcare delivery system refers to a health system's business plan to create a qualityoriented culture of providing safe and high quality care and reflects its commitment to apply the CCM across the organization. Features of this element include: (i) presence of clinician leaders who are dedicated members of the team and who visibly support improvement at all levels of the organization, beginning with the senior leader, (ii) promoting effective improvement strategies aimed at comprehensive system change, (iii) encouraging open and systematic handling of errors and quality problems to improve care, (iv) providing incentives based on quality of care and (v) developing agreements that facilitate care coordination within and across organizations.
Community linkage refers to mobilizing or developing community resources and policies to support healthy lifestyles and the needs of patients. Community resources help bolster health systems efforts to keep chronically ill patients supported, involved and active. Features of this element include: (i) encouraging patients to participate in effective community programmes, (ii) forming partnerships with community organizations to support and develop interventions that fill gaps in needed services and (iii) advocating for policies that improve patient care.
Self-management support refers to empowering and preparing patients to manage their health care. Patients are encouraged to set goals, identify barriers and challenges, and monitor their own conditions. A variety of tools and resources provide patients with visual reminders to manage their health. Features of this element include: (i) emphasizing the patient's central role in managing their health, (ii) using effective self-management support strategies that include assessment, goal setting, action planning, problem-solving and follow-up and (iii) organizing internal and community resources to provide ongoing self-management support to patients.
Delivery system design refers to assuring effective, efficient care and self-management support in care delivery. Features of this element include: (i) regular, proactive planned visits which incorporate patient goals to help individuals maintain optimal health and allow health systems to better manage their resources, (ii) visits often employ the skills of several team members with defined roles and tasks, (iii) using planned interactions to support evidence-based care, (iv) providing clinical case management services for complex patients, (v) ensuring regular follow-up by the care team and (vi) giving care that patients understand and that agrees with their cultural background.
Decision support refers to promoting care consistent with evidence-based, effective care guidelines and patient preferences. Features of this element include (i) clinicians have convenient access to the latest evidence-based guidelines for care for each chronic condition, (ii) continual educational outreach to clinicians to reinforce utilization of these standards, (iii) embedding evidence-based guidelines into daily clinical practice, (iv) sharing evidence-based guidelines and information with patients to encourage their participation, (v) using proven provider education methods and (vi) integrating specialist expertise and primary care.
Clinical information systems refer to organizing data to facilitate efficient and effective care. Features of this element include: (i) health systems that harness technology to provide clinicians with an inclusive list (registry) of patients with a given chronic disease. A registry provides the information necessary to monitor patient health status and reduce complications, (ii) providing timely reminders for providers and patients, (iii) identifying relevant subpopulations for proactive care, (iv) facilitating individual patient care planning, (v) sharing information with patients and providers to coordinate care and (vi) monitoring performance of practice team and care system.
Previous systematic reviews and meta-analyses showed research gaps and mixed results in evaluating CCM interventions in patients with type 2 diabetes for patient outcomes such as hemoglobin A1c (HbA 1c ), systolic blood pressure (SBP), diastolic blood pressure (DBP), low-density lipoprotein (LDL) cholesterol and body mass index (BMI). The HbA 1c measurement remains the primary tool for assessing glycemic control and risk for diabetes complications and mortality in medical evaluation [20][21][22][23]. Previous metaanalyses of CCM were based on a limited number of search databases and included non-randomized trials, patients with type 1 diabetes or studies limited to a continent [24][25][26][27][28][29][30]. Evidence from some systematic reviews showed a mixed impact on patient outcomes and processes of care [31][32][33][34], while other meta-analyses showed improvements in patient outcomes such as HbA 1c [35][36][37].
A retrospective cohort study in southern England using databases [38] showed that the rate of utilization of primary care services by people with type 2 diabetes increased from 2013 to 2020, but this increase did not correlate with better outcomes. The World Health Organization's Global Diabetes Compact [39], a global initiative, proposed strengthening primary health care for accessible diabetes treatment. It is therefore timely to perform an updated systematic review and meta-analysis to enhance applicable knowledge for the management of type 2 diabetes in primary care. Our study will update the literature search up to 2022 that examined CCM interventions compared with usual care and controls using patient outcomes such as HbA 1c , SBP, DBP, LDL cholesterol level and BMI in patients with type 2 diabetes receiving primary care.

Methods
This systematic review was conducted according to the Cochrane Handbook for Systematic Reviews of Interventions [40] and reported with reference to the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement [41]. The protocol of this systematic review was registered in the International Prospective Register of Systematic Reviews (PROSPERO CRD42021273959).

Literature search
For this review, a comprehensive search of randomized controlled trials (RCTs) from January 1990 (around when CCM was introduced) until 11 June 2021 was performed. Six databases, PubMed, Embase, CINAHL, Cochrane, Scopus and Web of Science, were searched. A two-phase search strategy was used for this review. In the first phase, an initial search of PubMed was performed using the following keywords and Medical Subject Headings (MeSH) terms: Diabetes Mellitus, Type 2, Models, Theoretical, Disease Management, Patient Care Team, Patient-Centred Care, Patient Care Management, Self Care, Self Efficacy, Delivery of Health Care, Self-Management and Chronic Disease. The search terms used in this study are shown in Additional file 1. Studies appearing to fit the eligibility criteria were retrieved. From these, relevant keywords and MeSH terms that were used in these studies were identified and compiled for a more thorough search to ensure that relevant studies on the topic were not missed. Through the studies identified in the first phase, a list of relevant keywords and MeSH terms was compiled. This was then used in the second phase, where the six databases, as identified above, were searched from January 1990 until June 2021. A manual search was also performed by searching the reference lists of eligible papers. An abbreviated search update was performed (2021 to 28 April 2022) using the PubMed, Embase and CINAHL databases.

Inclusion criteria
Studies were included if they met the following criteria: (i) non-pregnant adult patients 18 years old and above with type 2 diabetes receiving care in primary care; (ii) interventions that included CCM elements such as the organization of the healthcare delivery system, community linkages or resources, self-management support, decision support, delivery system design and clinical information systems; (iii) usual care as control; (iv) postintervention HbA 1c level as outcomes; and (v) RCTs. For studies that did not describe the CCM elements within the interventions, two reviewers, LHG and CJRS, did so based on the published description of CCM elements as described [19].

Exclusion criteria
Studies were excluded if they involved (i) children; (ii) acute diseases, cardiovascular diseases, chronic respiratory diseases, human immunodeficiency virus, mental health disorders, chronic pain and cancer and (iii) hospital or nursing homes. Usual care refers to standard of care for patients with type 2 diabetes. Studies that included additional interventions into their usual care will be excluded.

Selection of studies
The selection process is reported using a PRISMA flow diagram [41]. The studies identified were exported to EndNote X9.3.3, where duplicate records were removed manually [42]. Two reviewers (LHG and CJRS) independently screened the titles and abstracts against the eligibility criteria and removed irrelevant records. Studies that appeared to fit the above criteria were retrieved in full for further assessment by the two reviewers, and irrelevant records were removed. Publications generated from the same study were linked together. When published information was insufficient to decide whether to exclude or include the study, the authors of these studies were contacted to acquire the necessary information. LHG and CJRS validated the final list of included studies. A third reviewer (WWST) was consulted if disagreements between LHG and CJRS were not resolved through discussion.

Data extraction
Reviewer LHG extracted and summarized relevant data of included studies using the standardized data extraction sheet according to the Cochrane Handbook for Systematic Reviews of Interventions [43] with details such as the author's details, year of publication, country, study design, setting, participants' characteristics, intervention, number and type of CCM elements used, control, sample size, attrition rate, outcomes and number included in the analysis. Both primary and secondary outcomes were extracted. When the outcomes were reported and presented as continuous data, the mean and standard deviation (SD) were extracted for both the control and intervention groups at follow-up. When the studies reported more than one follow-up period, data were only extracted for the latest follow-up from the start of the intervention. Where data were not reported as the mean and SD, such as if the authors reported the results as the median and interquartile range, we contacted the author of the study to request the relevant data. If there was no response from the authors, the quantile method from Wan et al. [44] was used to calculate the mean and SD.

Quality assessment
The methodological quality of the included studies was assessed independently by two reviewers (LHG and CJRS) using the Cochrane Collaboration's risk of bias tool [40]. This tool assessed each study for random sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcome assessment, incomplete outcome data and selective reporting. Any disagreements between the two reviewers were resolved through discussion with a third reviewer (WWST). The risk of bias graph and summary were generated by Review Manager (RevMan) software 5.4.1 [45].

Data synthesis
The primary outcome of this review was HbA 1c . The secondary outcomes were SBP, DBP, LDL cholesterol and BMI. All outcomes were expressed as the mean differences (MD) with 95% confidence interval (CI). The results were considered statistically significant when p<0.05. The results were pooled using DerSimonian and Laird's random-effects model. RevMan software was used to conduct meta-analyses and graph generation. The heterogeneity of the selected studies was evaluated using χ 2 and I 2 statistics [46]. Using the χ 2 test, significant heterogeneity between studies was considered significant if p<0.10 [47]. Using I 2 statistics, 0-40% represents no importance, 30-60% moderate heterogeneity, 50-90% substantial heterogeneity and 75-100% considerable heterogeneity [46]. Subgroup analysis explored the effectiveness of CCM across baseline HbA 1c levels, study duration and numbers of CCM elements. The baseline HbA 1c at 8% was chosen as a less stringent treatment goal in consideration of the heterogeneity of preferences for intensity and mode of glucose control in older adults with type 2 diabetes [48][49][50][51]. Publication bias was explored using a funnel plot and Egger's test [52].

Search results
A total of 16,911 records were identified through an electronic database search (16,842 records) and other methods (69 records) including the abbreviated search. After removing 5723 duplicate records, 11,188 records were identified for screening. Thirty-two records were excluded as they were published before January 1990. Using title screening, another 10943 records were excluded. The remaining 213 records were screened using abstract and full text with 196 records excluded by the screenings. Abstract screening excluded 124 records with reasons such as (i) participants were not type 2 diabetic (nine studies), (ii) non-experimental study (90 studies), (iii) non-primary care settings, e.g. hospital setting (10 studies), (iv) interventions not related to CCM (14 studies) and (v) non-clinical related outcomes (one study). Full text screening excluded 72 records with reasons such as (i) participants were not type 2 diabetic (seven studies), (ii) non-experimental study (13 studies), (iii) non-primary care settings, e.g. hospital setting (14 studies), (iv) interventions not related to CCM (17 studies), (v) non-clinical related outcomes (three studies) and (vi) limited information on interventions and results (18 studies). Examples of limited information were mainly (i) no information on sample size for groups, (ii) HbA 1c levels not available and (iii) means or percentages provided without standard deviations or standard errors for HbA 1c levels and other readings. In total, 17 records [53][54][55][56][57][58][59][60][61][62][63][64][65][66][67][68][69] were included for this review (see Fig. 1). The PRISMA flow diagram is illustrated in Additional file 2 and the PRISMA checklist in Additional file 3. The funnel plot appeared symmetrical, suggesting no publication bias (see Additional file 4).
Usual care of the included studies was broadly described as (i) care provided by primary care physicians or practice nurse following good clinical practice involving routine medical evaluation, patient education on general care, use of home glucose monitoring, patients given a copy of their diabetes test results and follow-up calls to patients after visits [53-55, 58, 61-65, 68, 69] and (ii) physicians have access to relevant clinical guidelines [57,60,66]. Three studies described usual care as ordinary medical care by physicians without further descriptions [56,59,67].

Risk of bias
The risk of bias summary and graph are presented in Additional file 6. Eight studies were appraised as unclear risk due to lack of information about random sequence generation [53,58,[60][61][62][63][64]67], while 10 studies were graded as unclear risk due to insufficient information about allocation concealment [53, 54, 58, 60-63, 65, 67, 68]. Although it was not feasible to blind participants and personnel due to the nature of the interventions, the absence of blinding did not affect the objective outcomes. Therefore, all 17 studies were graded as low risk for blinding of participants, personnel and outcome assessment [70,71]. Under incomplete data, three studies [62,64,69] were rated as high risk, as ≥20% attrition rate observed in either or both arms posed a serious threat to the study's validity [72]. One study was rated as unclear risk, as the numbers of participants were not reported at randomization [57]. For selective reporting, 10 studies were assessed as low risk, while seven studies lacked clarity and were hence assessed as unclear risk [53,54,58,59,61,64,69].

Subgroup analysis
Subgroup analyses were performed for the primary outcome HbA 1c level. Subgroup analyses were stratified by participants' mean baseline HbA 1c levels, study duration and number of CCM elements in the interventions. Subgroup analysis revealed no significant subgroup difference for study duration (<12 months vs ≥12 months) (p=0.55) (see Additional file 9).

Discussion
This review assessed the effectiveness of the Chronic Care Model (CCM) for adults with type 2 diabetes in primary care on improving patient outcomes. Our results revealed that, in comparison to usual care, CCM interventions in primary care significantly improved HbA 1c and systolic and diastolic blood pressures but not LDL cholesterol or BMI.
The CCM is an integrated model that has been shown to be an effective framework for improving the quality of diabetes care through the implementation of its six core elements [73]. A five-year prospective cohort study using a multidisciplinary Risk Assessment and Management Programme-Diabetes Mellitus (RAMP-DM) for diabetic patients [74] incorporating CCM elements of risk-stratified care planning, multidisciplinary care, scheduled monitoring of complications, diabetes selfmanagement education and smoking cessation showed significant improvements for HbA 1c , systolic blood pressure, diastolic blood pressure, LDL cholesterol and body mass index readings between groups. Patients enrolled in the CCM intervention experienced a reduction in cardiovascular risks by 56.6%, microvascular complications by 11.9% and mortality by 66.1%. A 12-month randomized controlled trial involving a comprehensive diabetes programme that incorporated risk stratification, action planning, regular follow-up and patient engagement in self-care, improved HbA 1c and blood pressure levels for adults with diabetes in primary care clinics within a managed care organization [75]. The RAMP-DM programme also found that the CCM was a cost-saving intervention in managing diabetes in patients over five years [9].
The HbA 1c remains a recommended and relevant measure for the medical evaluation and clinical management of people with type 2 diabetes with the goals of treatment being to prevent or delay complications [20]. The UK Prospective Diabetes Study (UKPDS) [22] emphasized the importance of improving glycaemic control in order to reduce diabetes related microvascular complications in people with type 2 diabetes. A 2019 cohort study of 34,737 newly diagnosed patients [21] found that longer periods of early glycaemic exposure at HbA 1c levels 6.5 to <8.0% did not increase the risk of microvascular or macrovascular events during follow-up (the Legacy Effect), whereas longer periods of exposure to HbA 1c levels ≥8.0% were associated with an increasing risk of microvascular events. Moreover, HbA 1c levels ≥9.0% for early exposure periods >0-4 years were associated with an increasing risk of macrovascular events. Similarly, a 10-year observational follow-up of people with type 2 diabetes [76] who were originally randomized to intensive glycaemic control had significant long-term reductions in myocardial infarction (15 to 33%) and in all-cause mortality (13 to 27%) depending on whether sulfonylurea or insulin or metformin was given as initial pharmacotherapy.
The Action to Control Cardiovascular Risk in Diabetes (ACCORD) study found that the use of intensive therapy to target HbA 1c below 6% for 3.5 years in patients with type 2 diabetes who have established cardiovascular disease or additional cardiovascular risk factors, increased mortality and did not significantly reduce major cardiovascular events [77]. Although the 2022 ADA guidelines [78] recommends that the HbA 1c goal of <7% is appropriate for many non-pregnant adults without significant hypoglycaemia, there are different recommendations for adults with limited life expectancy or who are older [48]. Older adults who are otherwise healthy with few coexisting chronic conditions, intact cognitive function or function status are recommended to work towards lower glycaemic goals such as HbA 1c < 7.0-7.5%. On the other hand, it could be more appropriate for older adults who have multiple coexisting chronic conditions, cognitive impairment or functional dependence or people with limited life expectancy to aim for less stringent glycaemic goals such as HbA 1c < 8.0%.
In setting the glycaemic targets, the studies in this review used guideline recommendations and thus demonstrating the presence of the decision support element from the CCM. Two studies in this review [58,64] were conducted before the ACCORD study results were published and were based on prevailing international guidelines. Seven studies measured specific HbA 1c goals [53,55,59,60,62,65,66] with majority targeting 7% or below and three studies targeting 6.5% or below [55,62,66]. Five of these seven studies based their recommended targets on national guidelines [53,66] or international guidelines such as the ADA guidelines [55,65] or both [59], while the remaining two studies did not mention what was the source for the recommended targets [60,62]. In total, nine studies in this review did not specify any target HbA 1c goals as outcomes [54, 56-58, 61, 63, 67-69].
Though guideline recommendations for health care providers are tools that can be used to improve health outcomes, diabetes care should be individualized for each person in order to achieve optimal outcomes. Taking a CCM patient-centred care approach, glycaemic goals are recommended to be personalised based on the individual's medical conditions and preferences [79]. The element of delivery system design from the CCM advocates for collaborative, multidisciplinary teams to provide care for people with chronic diseases such as diabetes and to facilitate patients' self-management. The self-management system element from the CCM addresses the need for goal-setting and helps clinicians incorporate personalised HbA 1c goal-setting in the management of patients with type 2 diabetes. In this review, two studies demonstrated the self-management system element by having personalised or realistic goals for glycaemic control for different patients [54,64] while the remaining studies were less clear if personalised goals were set. In the first study, the intervention protocol was guided by a treatment algorithm (an aspect of the decision support element in CCM) that determined the frequency and intensity of patient care, based on level of diabetes control and patient's associated health risks including the use of higher cut-points for HbA 1c goals [54]. This study also demonstrated how the elements of decision support and self-management support were intertwined in the interventions using the CCM. In the second study, the intervention group incorporated realistic and best possible goals for glycated haemoglobin, blood pressure, and lipids within predefined categories [64]. In the remaining studies, three described aspects of patient-centred care such as patient-specific goal setting for glycaemic status, blood pressure and serum lipids [55], agreement on therapeutic goals in a shared patient-physician decision-making process [68] and shared treatment plan, shared decision-making and goal-setting [69]. Our review shows that the CCM can be used to address the gap in the lack of personalised goalsetting for the management of patients with type 2 diabetes, in particular for those who may experience adverse outcomes with intensive blood glucose control [77].
In our review, all except one trial contained the element of self-management support (see Table 1 and Additional file 5). This trial looked at computerized clinical decision support for providers and did not contain the element of self-management support for patients [57]. A systematic review by Si et al [25] reported that RCTs involving the self-management support element had a reduction in HbA 1c by −0.53% compared to usual care. The self-management support element of the CCM emphasizes that the patient is the main person responsible for managing their health and the healthcare provider works with the patient to jointly identify problems, set goals, establish priorities, and develop an action plan and strategy for solving the problems that have been identified. Empowering patient self-management is fundamental to the successful implementation of the CCM [18]. It is therefore not surprising that almost all studies in our review incorporated self-management support in the interventions. Other commonly occurring elements found in this review were decision support, delivery system design and clinical information systems, while the elements of organizational system design and community linkages were least observed (see Additional file 5), as similarly reported in other reviews [24,25,28,33,34,80,81]. Nonetheless, our review was not able to show that any single CCM element was found to be critical [24] or superfluous [82] to improve outcomes.
The CCM is about person-centred approach to managing chronic conditions such as diabetes. Therefore, HbA 1c should not be the only relevant measure in the management of people with type 2 diabetes nor be the key determinant of whether health systems should adopt the CCM or not. There should be focus on non-biochemical outcomes such as quality of life and reduction of complications, which have value in themselves, even if the HbA 1c outcome did not come down. In this review, five studies measured quality of life as an outcome [55,[59][60][61]67] with three studies [55,60,61] using the 36-item short-form health survey (SF-36) [83], and two studies [59,67] using SF-12 [84]. An additional measure, Diabetes-39 questionnaire was used to assess diabetes-related quality of life [85,86] for one study [59]. Four studies [55,59,60,67] showed there was no statistically significant change in quality of life measures between groups though there was a positive trend in one study [59]. One study [61] showed statistically significant increases in four scales of the SF-36, namely, the role limitation due to physical problems and social functioning, the role limitation due to emotional problems and the physical component summary score.

Blood pressures and BMI outcomes
Looking at the effect of CCM interventions on the secondary outcomes in this review, adults with type 2 diabetes and hypertension were found to have improved systolic and diastolic blood pressures. A probable reason could be the patients' ability to perform self-management. Those who are able to perform their glucose or blood pressure measurement readily at home to enable selfmonitoring would gain better control of their condition [87,88]. Conversely, patients with hyperlipidaemia were only able to assess their progress through blood tests in the clinics and hence it may reduce their level of self-management. More research is recommended to affirm this finding. Other reviews also found small gains in cholesterol improvement that could be clinically trivial [29,30,36]. Our study also did not find any improvement in BMI.

Subgroup analyses Baseline HbA 1c levels
The baseline HbA 1c level was shown in this meta-analysis to affect HbA 1c outcomes, with the group having a mean baseline HbA 1c ≥8% showing greater reductions in HbA 1c changes than the <8% group. This finding concurs with three other meta-analyses [26,27,37] except one [30]. A 2017 systematic review [89] established that the HbA 1c measurement is a reliable risk factor of all-cause and cardiovascular mortality in diabetics and non-diabetics. The review recommended that the optimal HbA1c levels for the lowest all-cause and cardiovascular mortality were 6.0 to 8.0% in people with diabetes and 5.0 to 6.0% in those without diabetes. In addition, a 2019 cohort study demonstrated that longer periods of exposure to HbA 1c levels ≥8.0% were associated with increasing microvascular and mortality risk [21]. Another study targeting the patients with a higher HbA 1c level showed that there were benefits from having fewer major cardiovascular events [90]. Our results suggest that CCM interventions could be strategically targeted on patients with HbA 1c levels ≥8.0% instead of those with lower readings.

Numbers of CCM elements
The majority of the studies in this review contain four or more CCM elements. A greater number of CCM elements was found to have better improvements in HbA 1c levels in this review, which is consistent with previous reviews suggesting a greater benefit of interventions with more CCM elements over a single element for type 2 diabetes [28,29,[91][92][93], while other reviews did not show the benefits or were inconclusive [24,25,73,81,82]. Elissen et al. [28] found that the most notable improvement in HbA 1c of −0.7% (95% CI −1.2, −0.3, p=0.22) was attained by trials having at least three CCM elements. Conversely, having two and fewer CCM elements may reduce the opportunities for education sessions, assessment of the patients' needs and identifying barriers to self-management [28]. While CCM has been promoted as a package of interventions supported by evidence that interventions with multiple elements do better than single ones, it is challenging to standardize the combinations of CCM elements [28]. More research is needed to provide evidence for supporting synergistic effects than the sum of the parts, with the CCM elements being interdependent and building on one another [14,82].

Length of intervention
Our review did not find any difference in mean HbA 1c reduction between trials lasting <12 months vs ≥12 months, similar to other meta-analyses [27,28,37]. This could be due to the few studies in the <12 months group in our review, resulting in an uneven distribution of the covariates [94]. Moreover, two studies in this review were much longer than 12 months with one lasting 18 months [63] and the other lasting six years [64]. One study was shorter than six months at 28 weeks [62]. These studies were included in the meta-analysis because there is no recommended duration for CCM to be carried out. Pimouguet et al. [27] and Elissen et al [28] found that studies shorter than 12 months were found to report more promising effects on glycaemic control than those longer than 12 months, although the difference did not achieve statistical significance, while Murphy et al. [37] found no difference. Other meta-analyses using groups of ≤12 months vs >12 months also did not find any significant difference in mean HbA 1c reduction between groups [30,36], though the reduction was greater in the >12 months duration group. Pimouguet et al [27] reasoned that effective features of disease management (ability of disease managers to start or modify medical treatment) could have impacted outcomes, irrespective of study duration or baseline HbA 1c levels.
Our meta-analysis shows that studies <12 months [58,59,61,62,69] showed a significant improvement results while those 12 months [53-57, 60, 65-68] and longer [63,64] may suggest sustainability of HbA 1c improvement using CCM. Diabetes is a long-term condition and it is important to show that CCM interventions can sustain the improved glycaemic control over the longer duration of its management.
This review has limitations. First of all, the majority of studies did not classify the CCM elements in the interventions. Although the two reviewers independently determined the numbers and type of CCM elements in the studies using a guide from the CCM developers, this could still lead to misclassification bias [95]. The varying numbers and types of CCM elements added to the heterogeneity, which could also be explained by the different intervention durations and baseline HbA 1c levels in the studies. Information about the randomization procedure and allocation concealment from healthcare providers was often missing, thus affecting the methodological quality of this review. There is a broad variety of usual care for the studies being reviewed and it may not be possible to have a standard of care that is similar for all studies. The review also focussed on improvements in biomedical parameters, not other outcomes such as quality of life. However, measuring biomedical outcomes remains important from some perspectives, as they are predictors of diabetes-related complications which in turn, are key determinants of healthcare costs and quality of life downstream. In this review, only two studies incorporated personalised goals as part of their intervention for diabetes management [54,64]. Most of the studies identified used a fixed goal for HbA 1c rather than personalised goals as would be recommended today, based on evidence of adverse effects of intensive control in some individuals with type 2 diabetes [77]. Therefore, more research is needed to evaluate the effectiveness of personalised goals in diabetes management. While our analysis shows that application of the CCM can result in changes in biomedical parameters in the intended direction, there is no direct empirical evidence that CCM would achieve the same impact in the context of personalized goals. Lastly, the effects of the interventions on biomedical parameters are relatively small and in themselves may not be clinically significant as compared to other interventions like pharmacological therapy which typically lower HbA 1c levels 0.5-1%.
More research on CCM interventions is needed for adults with hyperlipidaemia and those who are overweight or obese, as these are not found to be significant in this study. Future research investigating the effectiveness of CCM should clearly classified the elements in the interventions and the descriptions of each CCM element should be better standardized. Research should also measure the effectiveness of the different CCM elements by themselves. Other CCM elements that are not well explored such as the the organization of the healthcare delivery system and community linkages should be investigated in future research. It is recommended for future studies that usual care be clearly described as being different from the interventions. The duration of the CCM intervention should also be investigated for its effectiveness on the outcomes, preferably for longer than 12 months to see if the effects can be sustained. Lastly, while it remains important to measure biochemical outcomes such as HbA 1c , in particular by setting personalized targets, other measures looking at patient-centred care such as quality of life, reduction of complications and quality of care should also be examined.

Conclusions
This systematic review and meta-analysis suggests that CCM is effective in primary care adults with type 2 diabetes for HbA 1c and blood pressure outcomes. However, CCM interventions did not significantly affect LDL cholesterol or BMI. While there was a greater reduction in HbA 1c levels when four or more CCM elements were used in the interventions compared with fewer elements, there was no influence of study duration on HbA 1c levels. The elements of self-management support, decision support, delivery system design and clinical information systems were found to be most commonly used in the interventions.